The social media app development company that engineers the feed, real time, and safety to scale.

We are specific where most pages wave at AI recommendations. A new app starts with a chronological feed, which is honest and cheap to run. At scale, a personalized feed is a retrieval and ranking system: a two-tower model learns user and item embeddings, approximate-nearest-neighbor retrieval with a library like FAISS or ScaNN pulls a few hundred candidates in milliseconds, and a heavier ranking model orders them, all targeting sub-100ms. We combine collaborative and content-based signals, and every model passes an evaluation gate before it reaches users. We build the data and serving layer first, so when the algorithmic feed goes in, it is measured instead of assumed.

A social platform now carries real duties. The EU Digital Services Act requires a statement of reasons for takedowns, notice-and-action and appeals, and transparency reports, and Very Large Online Platforms add systemic-risk assessments, recommender transparency with a personalization opt-out, and audits, with fines up to 6% of global turnover. In the US, the amended COPPA rule governs data from children under 13, and the REPORT Act requires reporting child sexual abuse material to the NCMEC CyberTipline as soon as reasonably possible. Roughly half of US states now have some age-verification or age-appropriate-design requirement. We scope which apply to your markets and build moderation, reporting, and age assurance into the architecture from the start.

Chat, presence, and notifications are a fan-out problem, so we engineer for it instead of hoping a single server holds. We build the real-time layer on WebSockets, with Redis Pub/Sub to fan messages out across connections and a message queue such as Kafka for high-throughput events. Presence and typing indicators are designed to stay cheap at scale, and notifications run through FCM and APNs. We model the read-heavy access patterns a social graph creates, and we load-test the system the way a viral moment would, so the platform stays responsive when usage spikes instead of falling over at the worst possible time.

It depends on the phase and the feature scope, so we give a defensible estimate after a discovery phase, and we price in phases. As representative ranges, an MVP, meaning profiles, a basic feed, posting, and 1:1 chat, is a smaller, faster build, while a full-scale platform with an algorithmic feed, live streaming, automated moderation, and creator monetization is a larger one, and the infrastructure run-rate grows with scale. Our median to a working build is 90 days. On cost, Resourcifi's global delivery model typically lands about 70% below comparable onshore US agency rates, and you get senior, in-house engineers named in writing before you sign, not a rotating freelancer bench. These ranges are representative; the real number comes out of scoping your features.

We treat media as its own discipline because it is. Uploads go to object storage and serve through a CDN, and we run a transcoding pipeline, often AWS MediaConvert, to produce adaptive-bitrate renditions so playback is smooth across devices and networks. For live, we ingest over RTMP and deliver over low-latency HLS or WebRTC, choosing the transport against the latency your product needs, because a live shopping stream and a one-to-many broadcast have different tolerances. We design for spikes, so a stream that suddenly goes big keeps scaling smoothly, and we wire live chat, reactions, and gifting into the same path.

Yes, and we recommend it. You can build a social media app in phases, funding what you can validate: an MVP with profiles, a feed, posting, and chat to prove the core loop, then growth features such as an algorithmic feed and richer media, then full-scale capabilities like live streaming, automated moderation, and creator monetization. The architecture is designed for that path from day one, so moving from a chronological feed to a ranked one, or from basic moderation to a hybrid pipeline, is an upgrade rather than a rebuild. That keeps early spend disciplined while protecting the platform from the re-platforming that catches teams who build only for the MVP.